Job Description:As part of our continued investment in AI-driven innovation, we are looking for a
Staff AI Engineer to join our growing AI team. This is a hands-on role delivering innovative solutions for the healthcare enterprise. The ideal candidate will bring deep expertise in modern AI systems, multi-agent systems & frameworks, LLM-based architecture, and software engineering.
Key Responsibilities:- Architect and develop enterprise-scale multi-agent systems leveraging LLMs and autonomous agent frameworks using Google ADK, Agentspace, MCP, RAG, and A2A orchestration.
- Design and implement RAG pipelines using BigQuery and Vertex AI Engine for knowledge grounding and factually accurate responses.
- Optimize agents for orchestration, knowledge grounding, multi-step reasoning, and decision-making.
- Design and implement distributed training workflows, online inference systems, and low latency serving architectures optimized for real-world performance, using Google cloud-native services.
- Engineer scalable, secure, compliant and production-grade AI fabric and AI agent workflows using Vertex AI and modern cloud-native technologies.
- Create reusable agent orchestration layers, observability hooks, and governance frameworks that accelerate Agentic AI adoption across TAG brands.
- Partner with cross-functional stakeholders in translating business requirements into technical specifications.
- Own the full AI development lifecycle - from data collection and implementation to deployment and monitoring.
- Implement intelligent observability and automation strategies to ensure AI system reliability and performance at scale.
Qualifications & Experience:- BS in Computer Science, or related technology field or equivalent experience.
- 2+ years of experience in Agentic AI engineering.
- 4+ years of experience in AI/ML engineering
- 8+ years of experience in software engineering, or platform engineering
- Proven track record of building and deploying production-grade AI/ML systems at scale.
- Deep understanding of modern AI model architectures (e.g., transformers, diffusion models) and system design.
- Strong hands-on expertise with Vertex AI (including model training, pipelines, orchestration, deployment, and monitoring) and Google's Agentic AI stack.
- Hands-on with one or more of these agent orchestration frameworks: Google ADK/Agentspace,LangChain, LangGraph, LlamaIndex, CrewAI or AutoGen.
- Proficiency in Python, LLM integration workflows, MCP (Model Context Protocol) for tool integration and A2A (Agent-to-Agent) orchestration for multi-agent workflows.
- Expertise in distributed training, online inference, and low latency serving architectures.
- Experience with Kubernetes, Cloud Run, and Dataflow/PubSub for scalable deployment.
Preferred Qualifications:- Experience with AI governance frameworks and responsible AI practices (Vertex AI Model Monitoring, BigQuery logging, Looker dashboards).
- Contributions to open-source AI projects or publications in leading AI/ML conferences.
- Experience with multi-modal models and advanced optimization strategies & frameworks.
- Experience automating, architecting and governing production grade MLOps infrastructure to scale, optimize, and observe AI workloads.
Annual Salary Range: $170,000-$200,000/year, with a generous benefits package that includes paid time off, health, dental, vision, and 401(k) savings plan with match.
